64 Quotes by Jeff Dean

I think robotics is a really hard problem - to make robots that operate in sort of arbitrary environments, like a big conference room with chairs and stuff.

If you pass a lot of data through a teeny network, like 20 neurons, it'll do what it can, but it's not going to be very good.

Previously, we might use machine learning in a few sub-components of a system. Now we actually use machine learning to replace entire sets of systems, rather than trying to make a better machine learning model for each of the pieces.

We have way more unsupervised data in the world than supervised data.

Transportation, with self-driving vehicles, is going to be a big use of machine learning.

I think multimodal kinds of models are pretty interesting - like can you combine text with imagery or audio or video in interesting ways?

I do kind of think there's a bit of an overemphasis on - in the community - on sort of achieving ever-so-slightly better state-of-the-art results on particular problems, and a little underappreciation of completely different approaches to problems that maybe don't get state of the art because it's actually super hard and a pretty explored area.

I think there are sometimes issues with - no matter where you put a conference, there's always going to be constraints on that. For example, sometimes students studying in the U.S. have trouble leaving the U.S. to go to a conference. So if you hold it outside the U.S. in a particular place, that sometimes creates complications.

It's important to engage with governments around the world in how they're thinking about AI - to help inform them.